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Finance Monitor AI Agent

Pricing

Pay per event

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Finance Monitor AI Agent

Finance Monitor AI Agent

Developed by

harvest-org

Maintained by Community

Generates market reports based on user queries. By inputting a search query such as "How is Microsoft doing this week?", the actor fetches relevant financial data, analyzes it, and produces a structured market summary.

0.0 (0)

Pricing

Pay per event

0

Monthly users

1

Runs succeeded

>99%

Last modified

a month ago

You can access the Finance Monitor AI Agent programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

1# Start Server-Sent Events (SSE) session and keep it running
2curl "https://actors-mcp-server.apify.actor/sse?token=<YOUR_API_TOKEN>&actors=harvestlabs/finance-monitor-ai-agent"
3
4# Session id example output:
5# event: endpoint
6# data: /message?sessionId=9d820491-38d4-4c7d-bb6a-3b7dc542f1fa

Using Finance Monitor AI Agent via Model Context Protocol (MCP) server

MCP server lets you use Finance Monitor AI Agent within your AI workflows. Send API requests to trigger actions and receive real-time results. Take the received sessionId and use it to communicate with the MCP server. The message starts the Finance Monitor AI Agent Actor with the provided input.

1curl -X POST "https://actors-mcp-server.apify.actor/message?token=<YOUR_API_TOKEN>&session_id=<SESSION_ID>" -H "Content-Type: application/json" -d '{
2  "jsonrpc": "2.0",
3  "id": 1,
4  "method": "tools/call",
5  "params": {
6    "arguments": {
7      "researchRequest": "How is microsoft doing this week?"
8},
9    "name": "harvestlabs/finance-monitor-ai-agent"
10  }
11}'

The response should be: Accepted. You should received response via SSE (JSON) as:

1event: message
2data: {
3  "result": {
4    "content": [
5      {
6        "type": "text",
7        "text": "ACTOR_RESPONSE"
8      }
9    ]
10  }
11}

Configure local MCP Server via standard input/output for Finance Monitor AI Agent

You can connect to the MCP Server using clients like ClaudeDesktop and LibreChat or build your own. The server can run both locally and remotely, giving you full flexibility. Set up the server in the client configuration as follows:

1{
2  "mcpServers": {
3    "actors-mcp-server": {
4      "command": "npx",
5      "args": [
6        "-y",
7        "@apify/actors-mcp-server",
8        "--actors",
9        "harvestlabs/finance-monitor-ai-agent"
10      ],
11      "env": {
12        "APIFY_TOKEN": "<YOUR_API_TOKEN>"
13      }
14    }
15  }
16}

You can further access the MCP client through the Tester MCP Client, a chat user interface to interact with the server.

To get started, check out the documentation and example clients. If you are interested in learning more about our MCP server, check out our blog post.

Pricing

Pricing model

Pay per event 

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Actor initialization

$1.000

Starting of the actor

LLM Input

$0.010

Length of input query (only for users who do not supply an API key)